Single-cell qPCR






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RNAi – microRNA – siRNA Applications – miRNA normalisation






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MIQE and QM strategies in qPCR






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High throughput quantitative PCR – digital PCR






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High Resolution Melting – Epigenetics






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Data Analysis: qPCR BioStatistics & BioInformatics






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CNA – Circulating Nucleic Acids






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High-throughput Droplet PCR

Philip Day, Amelia Markey, Stephan Mohr
University of Manchester, United Kingdom

Abstract
The polymerase chain reaction has facilitated the ready analysis of nucleic acids. The depth of sequence analysis that can be reached via PCR is largely independent of sensitivity requirements, and more a function of the analyte intricacy within the biological sample. A next challenge requires the development of means to unravel the complexity of heterogeneous tissues. Avoidance of bulk measurement has been made possible through adopting principles of digital PCR where samples are diluted to achieve a homogeneous target, which is often presented as a single molecular target. This has presented the task of producing massively parallelized quantitative nucleic acid data from the cellular constituents of tissues. The generation of aqueous droplets in a two phase flow is shown to be readily and routinely facilitated by miniaturized fluidic devices. Droplets serve as ideal means to form discrete packages for the purpose of PCR, offering an enhanced handling potential by virtue of reactant containment, to concurrently eliminate both contamination and sample loss. The packaging into droplets also enables the measurement of nucleic acids from defined populations of cells from bio-samples, or molecules of nucleic acids from the individual nuclei of cells, by means of high throughput, single cell analysis. Details are provided for the production of microfluidic devices for both creating droplets and undertaking PCR in a continuously flowing microfluidic stream. Suggestions are also made as to the optimal fabrication techniques and the importance of device calibration to achieve the conditions favouring efficient PCR.


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Application of Microfluidic qPCR Arrays to the Profiling of miRNA Expression in Purified Hematopoietic Populations and in Single Cells

Oleh I. Petriv1, Florian Kuchenbauer2, Allen Delaney3, Veronique Lecault1, Adam White1, David G. Kent2, Lindsay Laycock2, Michael Heuser2, Tobias Berg2, Michael R. Copley2, Jens Ruschmann2, Sanja Sekulovic2, Frann Antignano2, Etsushi Kuroda2, Victor Ho2, Claudia Benz2, Timotheus Y. F. Halim2, Vincenzo Giambra2, Gerald Krystal2, Connie J. Eaves2, Fumio Takei2, Andrew P. Weng2, James M. Piret4, Marco A. Marra3, R. Keith Humphries2, Carl L. Hansen1
1 University of British Columbia, Canada; 2 Terry Fox Laboratory, BC Cancer Agency, Vancouver, BC; 3 Genome Sciences Centre, BC Cancer Agency, Vancouver, BC; 4 Michael Smith Laboratories,University of British Columbia, Vancouver, BC

Abstract

The hematopoietic system is comprised of a large number of highly specialized cell types that occupy distinct niches and which perform a diversity of functions ranging from innate immune response to oxygen transport. All these cell types are thought to be derived from a common stem cell and represent a hierarchal tree of differentiation. miRNA expression is a critical player in orchestrating this differentiation. Due primarily to technical limitations in the analysis of limited cell populations the program of miRNA expression across the hematopoietic tree is largely unknown. Here we report the development of a microfluidic RT-qPCR approach for global miRNA profiling in limited populations and apply this to expression analysis of 27 distinct cell populations from the murine hematopoietic system. Expression of 288 miRNAs in each population was measured in multiple replicates for a total of over 80,000 RT-qPCR assays using microfluidic qPCR arrays (Fluidigm Biomark™ Dynamic Array). Using synthetic miRNA standards the sensitivity and efficiency of each assay was calibrated to allow for accurate comparison of expression across species and populations. In addition we show this technique is capable of measuring up to 12 miRNA species at single-cell resolution. We demonstrate that global miRNA profiling of the murine hematopoietic tree allows for direct and independent reconstruction of the known hierarchal relationships. We further find that the number of miRNA species expressed in a cell population is not correlated with differentiation state and that miRNA expression patterns in stem cell and progenitor populations are closely related with major reprogramming upon commitment to a single lineage. Single cell measurements further show that miRNA expression levels are tightly regulated within highly purified populations, suggesting that miRNA may be suitable biomarkers for assessing heterogeneity in a given population.


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Detection and characterization of single circulating tumor cells as chance to monitor and individualize chemotherapy

Stephanie Carl, Torsten Kroll, Katharina Pachmann
Friedrich Schiller University Jena, Germany

Abstract

Individualization of chemotherapy for a cancer patient needs a lot of parameter testing in the beginning as well as during therapy. One of those parameters especially for the evaluation of metastasis is the determination of the amount of disseminated tumor cells in the blood circulation. Previously we developed a straightforward method for the detection, counting and imaging of circulating tumor cells from epithelial tumors. In the last years we could show the prognostic relevance of the change in the amount of CETCs due to the scheme of the chemotherapy for various tumor entities. With this established approach we have a tool for individual therapy monitoring. Our next goal is to gauge chemotherapy in accordance with the molecular characteristics and gene expression profiles of individual CTC`s. Therefore we implemented a straight forward single cell isolation protocol using the MMI CellEctor single cell sorting device. The presented work flow will allow us to investigate potential therapy targets depending on the genetic characteristics and expression status using single cell PCR.


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